In this work we apply a combination of computational and social science methods to evaluate abuse toward UK MPs on Twitter. We utilise a large tweet collection on which natural language processing analysis has been performed in order to identify abusive language. This methodology is presented in detail by Gorrell et al [1]} and summarised here. We then follow Braun and Clarke's [2]} process of thematic analysis on a subset of tweets that received 8% or more of abusive replies, in which at least 20 abusive replies were received. This analysis is described in more detail below.
